Team building criteria in software projects: A mix-method replicated study

Silva, Fábio Q. B. da; França, A. César C.; Suassuna, Marcos; Mariz, Leila Maria Rodrigues de Sousa; Rossiley, Isabella; Miranda, Regina; Gouveia, Tatiana B.; Monteiro, Cleviton V. F.; Lucena, Evisson; Cardozo, Elisa S.F.; Espindola, Edval

doi:10.1016/j.infsof.2012.11.006

Cited by 52 publications

(42 citation statements)

References 34 publications

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“…Eighteen studies show that team skill and domain knowledge are common selection criteria in Agile team formation [72]. For instance, excellent domain knowledge has been found to contribute to the success of XP use [73].…”

Section: ) Development Teams' Domain Knowledgementioning

confidence: 99%

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Key Factors for Selecting an Agile Method: A Systematic Literature Review

Alqudah¹,

Razali²

2017

International Journal on Advanced Science, Engineering and Information Technology

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Abstract-Agile methods have become popular in recent years because the success rate of project development using Agile methods is better than structured design methods. Nevertheless, less than 50 percent of projects implemented using Agile methods are considered successful, and selecting the wrong Agile method is one of the reasons for project failure. Selecting the most appropriate Agile method is a challenging task because there are so many to choose from. In addition, potential adopters believe that migrating to an Agile method involves taking a drastic risk. Therefore, to assist project managers and other decision makers, this study aims to identify the key factors that should be considered when selecting an appropriate Agile method. A systematic literature review was performed to elicit these factors in an unbiased manner, and then content analysis was used to analyze the resultant data. It was found that the nature of the project, development team skills, project constraints, customer involvement and organizational culture are the key factors that should guide decision makers in the selection of an appropriate Agile method based on the value these factors have for different organizations and/or different projects.

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Section: ) Development Teams' Domain Knowledgementioning

confidence: 99%

“…Team's domain knowledge is considered as an important factor in the selection of Agile methods [72], [74]. Also, inappropriate selection of the practices in an Agile method leads to poor implementation [72], [116].…”

Section: ) Development Teams' Domain Knowledgementioning

confidence: 99%

Key Factors for Selecting an Agile Method: A Systematic Literature Review

Alqudah¹,

Razali²

2017

International Journal on Advanced Science, Engineering and Information Technology

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“…Performance: Team composition was identified as a performance factor in five studies [27,34,32,43,11]. One study stated that personality diversity was among the strongest predictors of project success [43].…”

Section: Groupmentioning

confidence: 99%

“…Another study concluded that the more degrees of freedom in the composition process the better the result will be, but that there is always a tradeoff between including the best available experts from different sites and the corresponding communication and coordination problems [27]. A systematic mapping survey showed that team composition criteria related to human factors, such as personality and behavior, presented the strongest correlations to project success [11]. Agile development: Three papers studied group think in relation to agile development.…”

Section: Groupmentioning

confidence: 99%

Towards a behavioral software engineering

Lenberg

Feldt

Wallgren

2014

Proceedings of the 7th International Workshop on Cooperative and Human Aspects of Software Engineering

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Throughout the history of Software Engineering (SE) it has been repeatedly found that the humans involved, i.e. the engineers and developers in addition to other stakeholders, are a key factor in determining project outcomes and success. However, the amount of research that focuses on human aspects has been limited compared to research with technology or process focus. With increasing maturity of the field, interest in agile methods and a growing dissatisfaction with the continued challenges of developing high-quality software on time, the amount of SE research putting human aspect in primary focus has increased.In this paper we argue that a synthesized view of the emerging human-focused SE research is needed and can add value through giving focus, direction and help identify gaps. Taking cues from the addition of Behavioral Economics as an important part of the area of Economics we propose the term Behavioral Software Engineering (BSE) as an umbrella concept for research that focus on behavioral and social aspects in the work activities of software engineers. We propose that a model based on three units of analysis can give structure and point to concepts that are important for BSE. To add detail to this model we are conducting a systematic review to map out what is currently known. To exemplify the model and the area we here present the results from a subset of the identified concepts.

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“…Moreover, other researchers believe that the numerous models that have been suggested for team composition have been shown not to yield positive results by scholars and organizations. 9,11,[20][21][22] This raises another challenge for researchers to identify and solve: the reasons for contradictory fits. For example, the problem may exist in team composition models where different researchers accentuate different personality types for effective teamwork, without adequately considering their suitable and effective role in actual teamwork.…”

mentioning

confidence: 99%

Finding an effective classification technique to develop a software team composition model

Gilal

Jaafar

Capretz

et al. 2017

J Software Evolu Process

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Ineffective software team composition has become recognized as a prominent aspect of software project failures. Reports from results extracted from different theoretical personality models have produced contradicting fits, validity challenges, and missing guidance during software development personnel selection. It is also believed that the technique/s used while developing a model can impact the overall results. Thus, this study aims to (1) discover an effective classification technique to solve the problem and (2) develop a model for composition of the software development team. The model developed was composed of 3 predictors: team role, personality types, and gender variables; it also contained 1 outcome: team performance variable. The techniques used for model development were logistic regression, decision tree, and rough sets theory (RST). Higher prediction accuracy and reduced pattern complexity were the 2 parameters for selecting the effective technique. Based on the results, the Johnson algorithm (JA) of RST appeared to be an effective technique for a team composition model. The study has proposed a set of 24 decision rules for finding effective team members. These rules involve gender classification to highlight the appropriate personality profile for software developers. In the end, this study concludes that selecting an appropriate classification technique is one of the most important factors in developing effective models.

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Team building criteria in software projects: A mix-method replicated study

Cited by 52 publications

References 34 publications

Key Factors for Selecting an Agile Method: A Systematic Literature Review

Key Factors for Selecting an Agile Method: A Systematic Literature Review

Towards a behavioral software engineering

Finding an effective classification technique to develop a software team composition model

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